GPT Agents

• Finished the token compare code and ran it on the blame_feeling data
• Tried to work on the online version of the paper but it was just too frustrating. Working local for now
• 1:00 Talk at NIST
• 3:00 meeting
  • No chess data
  • explain that we are selecting text strings, which contain but are not limited to hashtags
  • Focus on the simulated output instead of token rank
  • Try sentiment analysis: machinecurve.com/index.php/2020/12/23/easy-sentiment-analysis-with-machine-learning-and-huggingface-transformers/
  • pahulpreet86.github.io/sentiment-analysis-methods-and-pre-trained-models-review/

import flair
from flair.models import TextClassifier
flair_sentiment = TextClassifier.load('en-sentiment')
text="Avengers: Infinity War is a giant battle for which directors Anthony and Joe Russo have given us touches of JRR Tolkien’s Return of the King and JK Rowling’s Harry Potter and the Deathly Hallows. The film delivers the sugar-rush of spectacle and some very amusing one-liners."
sentence=flair.data.Sentence(text)
flair_sentiment.predict(sentence)
total_sentiment = sentence.labels
print(total_sentiment)

Output:
[POSITIVE (0.9994151592254639)]

SBIR

• Sprint planning
• Trying to get a charge number for the RFI response – done
• Finished the response